The invention relates to a server, a system and a method for determining a position of an end of a traffic jam.
A server for determining a location statement for a traffic jam is known from the prior art. Google Traffic can determine the geographical area in which a traffic jam has occurred. In this case, the server evaluates the speed of smartphones situated in vehicles, for example. These traffic jam data indicate the location of the traffic jam only with excessive inaccuracy, however. The type of the traffic jam, future development thereof or the most recent development to have dynamically taken place cannot be determined using the Google Traffic approach.
Another way of determining the location of the traffic jam is to install stationary sensors, such as cameras or induction loops, on a relevant section of road. These stationary sensors evaluate the traffic state, particularly the traffic flow and the traffic density. In this case, the speed and the distances between the individual vehicles are measured and the traffic flow and the traffic density are computed therefrom.
A disadvantage of this type of location determination is that the position of the end of the traffic jam can be computed only in the section of road in which the sensors have been installed. The installation of stationary sensors, such as cameras or induction loops, is very expensive and therefore not used extensively.
EP 1 235 195 A2 describes a method for determining traffic jam data. In this case, a first vehicle transmits its current position, which is coupled to a time statement, to a control center. The control center stores this information in a database and uses the data to determine a route of the first vehicle. Using further routes of other vehicles that are in the vicinity of the first vehicle and are likewise stored in the database, the control center produces a route forecast for the first vehicle. This route forecast provides information about how the speed of the first vehicle will change in all likelihood on the forthcoming route section. The precise location, the behavior of the traffic jam and the position of the end of the traffic jam cannot be ascertained with this approach either.
US 2007/0005231 A1 describes a system and a method for determining the position of an end of a traffic jam. A vehicle associated with the system comprises a controller that is used to analyze the speed of the vehicle. As soon as the vehicle, traveling at constant speed, approaches an end of a traffic jam and therefore reduces its speed, the controller stipulates the end of the traffic jam as being at the position at which the speed of the vehicle is approximately zero or is constantly at a very low speed level. This has the disadvantage that the position of the end of the traffic jam can be determined only very inaccurately. If there is, by way of example, a very soft end of the traffic jam at which the speed firstly decreases steadily but secondly does not assume the value zero or does not reach a very low and constant level, then this system and method cannot be used to effect exact position finding for the end of the traffic jam.
Against the background of this prior art, the object arises of providing a server, a system and a method that address the aforementioned disadvantages. In particular, the aim is to provide a server that determines the exact position of the end of the traffic jam and possibly the development thereof extensively and independently of location. In this case, the aim is for exact position finding for the end of the traffic jam to be effected even in the case of soft ends of traffic jams that the vehicles enter steadily at ever slower speed. A further object is to provide a server for determining the position of the end of the traffic jam that is capable of determining the type of the end of the traffic jam, for example, determining whether it is necessary to brake sharply on entering the end of the traffic jam (a “hard end” of the traffic jam), or whether a slow speed reduction be assumed (i.e., a soft end of the traffic jam).
The object is achieved by a server for determining a position of an end of a traffic jam that comprises                a computer unit;        a memory;        a reception unit for receiving a multiplicity of measurement data, in each case with at least one position data statement for a vehicle.        
In this case, the server is preferably designed to use at least one sigmoid function and to use the received measurement data in order to compute the position of the end of the traffic jam.
The at least one sigmoid function sig(x) used to locate and characterize the position of the end of the traffic jam may have the following formula, for example:
      sig    ⁡          (      x      )        =                    a        1                    1        +                  e                                    a              2                        ⁡                          (                                                a                  3                                -                x                            )                                            +          a      4      
This may, as depicted, be defined on the basis of four parameters [a1, a2, a3, a4].
The sigmoid functions in this case, for example in a first iteration cycle, may be determined by randomly chosen parameter values. The measurement data can be used to select at least one sigmoid function that models the real traffic jam profile and hence also the end of its traffic jam well. The selected and hence high quality sigmoid function may be used to compute the position of the end of the traffic jam.
Alternatively or additionally, parameter values of the sigmoid functions may be determined or computed on the basis of at least some of the measurement data. The measurement data are, by way of example, transmitted by a vehicle via a radio network, preferably a mobile radio network, to the server, which stores them in its memory. The measurement data may comprise a position data statement for a vehicle which may be used by the computation unit to compute the speed of the vehicle on the basis of the time of transmission of the position data statements.
An advantage of the server according to the invention is that it can use the sigmoid function to determine the position of the end of the traffic jam, regardless of the position from which the vehicle sent its measurement data to the server. The sending vehicle may still be situated before or even just a short way after the position of the end of the traffic jam. The sigmoid function is thus suited to being able to make statements about the end of the traffic jam even using measurement data from any positions, for example within the traffic jam.
A further advantage is that the profile of the sigmoid function may be used to determine how the speed of the vehicle changes over time. This may be used to characterize the end of the traffic jam. If the sigmoid functions has a rapid and sharp fall in the profile, then a hard end of the traffic jam is involved, in which vehicles encounter, from unrestricted travel, a buildup of, by way of example, stationary vehicles. If the sigmoid function has a slow and shallow fall in the profile, then this indicates that the end of the traffic jam is entered with a slow speed reduction with surrounding vehicles, and hence there is a soft end of the traffic jam. The server may be designed to convey corresponding knowledge to subscribers, for example vehicles, that have subscribed to this service. The server can also use this knowledge to make statements about the dangerous nature of the traffic jam. By way of example, multiple danger categories (e.g. high, low, slight) may be defined, with the server dividing up the respective traffic jam into one of these categories.
Preferably, the measurement data are data tuples and comprise:                traffic information data; and/or        speed data that indicate at least one speed of the respective vehicle; and/or        distance data that indicate at least one distance between the respective vehicle and a vehicle traveling ahead of the respective vehicle; and/or        braking frequency data that indicate a braking frequency of the respective vehicle.        
This allows the server to use the measurement data to determine the surroundings of the vehicle, such as the traffic density, for example. By way of example, transmission of the distance to a vehicle traveling ahead allows the server to compute the traffic density. The traffic density can in this case be computed using the following formula, for example:
  ρ  =      1          r      +      s      
In this case, the traffic density ρ is dependent on the distance r between two vehicles and the vehicle length s of the rear vehicle. The same computation may also be provided by the traffic information data, which indicate the number of vehicles in the vicinity of the vehicle or lane changing behaviors or other data relating to the traffic, for example. Similarly, it is also possible for the traffic density to be computed on the basis of the braking frequency of the vehicle. Determination of the traffic density may also be based on the entire detected surroundings of the measuring vehicle. Hence, it is also possible for the position of the end of the traffic jam to be computed by virtue of the change in the traffic density profile.
A further advantage of the invention is that the sigmoid function may be used to continuously model the traffic density over the route, preferably also over time. This allows the position of the end of the traffic jam to be determined with few measurement points, regardless of the position at which the measurement points or measurement data have been captured. It is also possible to make a statement about the type of the end of the traffic jam. If the traffic density profile rises rapidly and sharply, then a hard end of the traffic jam is involved. If the sigmoid function has a slow and shallow rise in the profile, then a soft end of the traffic jam is involved. The server may be designed to convey corresponding information to subscribers, for example vehicles that have subscribed to this service. The vehicles may process this information and use it for outputting warning signals to the driver or to other road users. Furthermore, this information may be used to influence the operation of a driver assistance system. If need be, the driver assistance system may then reduce the speed of travel.
Advantageously, the measurement data may comprise hazard warning light data. These hazard warning light data may indicate the use of the hazard warning light system of the vehicle and/or the use of a hazard warning light system of a vehicle, as detected using a sensor and/or a camera, in the vicinity of the vehicle. These hazard warning light data may contribute to performance of more accurate determination of the position and/or of the characteristics of the end of the traffic jam.
In a further embodiment of the invention, the server is designed to determine a multiplicity of parameter sets in order to compute the position of the end of the traffic jam. Each parameter set defines a first sigmoid function and a second sigmoid function. The first sigmoid function of the parameter set models a speed profile and the second sigmoid function of the parameter set models a traffic density profile. A parameter set can in this case be determined by eight parameters [v1, v2, v3, v4, ρ1, ρ2, ρ3 ρ4], wherein four parameters [v1, v2, v3, v4] map the speed profile and four parameters [ρ1, ρ2, ρ3, ρ4] map the traffic density profile. The multiplicity of parameter sets may preferably be greater than 10, more preferably greater than 100 or greater than 1000. As a parameter set defines two sigmoid functions, the first sigmoid function depicting the speed profile of the vehicle on the basis of the location and the second sigmoid function depicting the traffic density profile on the basis of the location, the advantages of the speed profile and of the traffic density profile are thus combined.
A further advantage is that lane precision location can be used to determine the characteristics of the end of the traffic jam in a manner accurate to the traffic lane. The speed profile and the traffic density profile can lead to different results for the end of the traffic jam. The server can output as the result the position that the modeled speed profile prescribes or the position that the modeled traffic density profile prescribes. It is also possible to determine a mean value between the two ascertained positions of the end of the traffic jam as the final position of the end of the traffic jam, for example the position that lies exactly between the two determined positions. The parameter sets can be used to make precise statements about characteristics of the end of the traffic jam. In this context, the type of end of the traffic jam is determined by taking into account both the change in the speed and the change in the traffic density, so that more exact statements can be made. Advantageously, the sigmoid function can also be used to model an acceleration profile or deceleration profile and analogously to determine the profile of the acceleration via the location, so as to determine the position of the end of the traffic jam. Modeling of the acceleration profile likewise allows firstly the position of the end of the traffic jam to be computed exactly and secondly the characteristic of the end of the traffic jam to be determined.
In an advantageous embodiment, the server can comprise a rating unit. The rating unit rates the quality of at least one selection from a multiplicity, computed by the server, of sigmoid functions having different parameters at least using the measurement data. The measurement data are compared with the computed sigmoid functions. The closer the profile of the sigmoid function to the value to the measurement data, the higher the quality of the sigmoid function and the better it is rated. Such rating of the sigmoid functions can be effected by virtue of the sigmoid functions being put into a class system of 10 classes, for example, with class 10 containing the highest quality of sigmoid functions. Selection of preferred sigmoid functions, for example of sigmoid functions in higher classes, such as classes 9 and 10 or the best 5, particularly the best 50 or 500, allows the determination of the position of the end of the traffic jam to be simplified and the number of correctly identified position determinations to be increased. By way of example, it is also possible for the sigmoid functions to be rated on the basis of the measurement data by determining the residual of least square fitting between the sigmoid function and the measurement data and using the magnitude of the residual to rate the respective sigmoid function.
In one embodiment, the rating unit can compute the sigmoid functions by using a particle filter and/or a support vector machine (SVM) and/or a linear discriminant analysis (LDA). The particle filter is used to produce continual updates for the sigmoid functions by new measurement data. In this context, the particle filter approximates the a posteriori distribution of the state probabilities of the sigmoid functions by a finite set of parameters [v1, v2, v3, v4, ρ1, ρ2, ρ3, ρ4]. A sample set, the particles, approximates the probability density function using the sigmoid functions. In contrast to alternative approaches, the nonparametric form of particle filters means that they approximate any distributions. Similarly, a computed speed profile and/or traffic density profile can be interpolated by an m th degree polynomial, where m=3 is an advantageous choice. The coefficients of this polynomial can be interpreted together with other characteristics of the signal, such as the gradient of the speed over time or the gradient of the traffic density over time, as a point in an n-dimensional hyperspace. An SVM or LDA previously trained using training data is now capable of making a statement about the extent to which the computed sigmoid functions correspond to the measurement data of the vehicle. The advantages in this case can be found in the rapid and reliable rating and also the compact representation of the rating rules.
In a further form of the invention, the server can receive traffic jam data from a further server. The traffic jam data indicate an area at which a traffic jam has occurred. The traffic jam data are used to compute the sigmoid function. Such computation can be effected by virtue of the server computing the sigmoid function by making a parameter preselection, the parameter preselection being effected on the basis of the traffic jam data. This allows the computation of the sigmoid functions to be controlled in a suitable manner in advance. The traffic jam data actually allow a parameter preselection to be made that models only such sigmoid function profiles as have a higher quality at the outset than sigmoid functions that have been computed by a random selection of the parameters. This has the advantage that the computation of the sigmoid functions is optimized and the position of an end of the traffic jam is determined in an improved and more rapid manner.
Furthermore, the object is achieved by a system that comprises a server, as has been described in the preceding explanations, and vehicles, wherein the vehicles are designed to transmit measurement data to the server. Similar or identical advantages to those already described in connection with the server are obtained.
In a preferred embodiment, at least one vehicle may be designed to transmit measurement data at regular intervals of time. In a further preferred system, at least one vehicle can transmit measurement data when a corresponding request is received from the server. Similarly, a combination of regular measurement data transmission and measurement data transmission on request is possible. It is also possible for triggering to allow the at least one vehicle itself to transmit measurement data to the server. In this case, the triggering can have a function of various database management systems, in particular large relational database management systems, and a particular type of changes in data can prompt a stored program to be called that allows or prevents this change and/or performs further activities, such as transmitting selected measurement data to the server, for example. This ensures optimum and suitable measurement data transmission within the system.
In a further advantageous embodiment, the server may be designed to select at least one vehicle from a list of vehicles, particularly using traffic jam data, and to ask the selected vehicle to transmit measurement data. In this case, the server can ask all vehicles that are on the list to regularly transmit to it at least position data that are additionally assigned to the vehicles on the list. On the basis of these position statements, the server selects vehicles that are in a vicinity of the traffic jam known from the traffic jam data and asks said vehicles to send measurement data to it. A further option is for the server to start the measurement data request from vehicles only as soon it has information available about a traffic jam. In this case, the server can firstly request all measurement data for the vehicles that are shown on the list. Secondly, in a first step, the server can start a position request for all listed vehicles and store only the position of the vehicles on the list. Based on the traffic jam data, the vehicles would then be selected, with vehicles that are situated in the area of the traffic jam being able to be selected. If there are still no measurement data available from these vehicles, then in a second step the server can request said measurement data in order to compute the position of the end of the traffic jam. All options have the advantage of simplifying, optimizing and suitably ensuring the measurement data transmission between the vehicles and the server.
In a further preferred embodiment, the server may be designed:
a) to take the traffic jam data as a basis for determining not only a traffic direction but also a provisional position of the end of the traffic jam and/or of a traffic jam center and/or of a traffic jam start;
b) to determine a vehicle position and a vehicle direction of travel for a multiplicity of vehicles;
c) to use the vehicle position and the vehicle direction of travel to select at least one vehicle that is before the provisional position of the end of the traffic jam and/or of the traffic jam center, preferably before the provisional position of the traffic jam start, and is moving toward the end of the traffic jam.
As a result of the selection of vehicles that are situated at a position before the position of the end of the traffic jam and are traveling toward the latter, only such measurement data from vehicles as are also directly related to the position to be computed for the end of the traffic jam are used. Hence, the measurement data transmission is optimized and reduced still further.
In a further embodiment, the at least one vehicle can comprise at least one distance measuring unit. This distance measuring unit may be designed to measure the distance between the vehicle and a vehicle traveling ahead of the vehicle. The distance can be used to ascertain and/or transmit traffic information data. Such a distance measuring unit may be, by way of example, the front radar for the ACC (Adaptive Cruise Control), a laser, a camera or another unit that is suitable for measuring the distance from a vehicle traveling ahead. An advantage of such a distance measuring unit is that the distance values can model a traffic density profile. On the basis of the speed and the distance from the vehicle traveling ahead, the computer unit or the vehicle itself can determine the traffic density arising in the surroundings of the measuring vehicle.
In a preferred embodiment, the server may be designed to transmit the computed position of the end of the traffic jam to vehicles. This allows presentation of the position of the end of the traffic jam in the vehicle. This informs the driver about the exact position and/or also about the characteristic of the end of the traffic jam, for example by means of his navigation appliance. If the end of the traffic jam is situated after a blind curve, for example, or if a hard end of the traffic jam is involved, then the driver of the vehicle can be forewarned in good time, so that the risk of accident can be reduced.
Further, the object is achieved by a method for determining a position of a end of the traffic jam, particularly by a server as has been described in the preceding embodiments, and/or within a system as has been described in the preceding embodiments, comprising the steps of:                determining a multiplicity of parameter sets, wherein each parameter set defines a first sigmoid function and a second sigmoid function, wherein the first sigmoid function of the parameter set models a speed profile and the second sigmoid function of the parameter set models a traffic density profile;        receiving measurement data for at least one vehicle;        rating the quality of at least some of the sigmoid functions defined by the parameter sets based on the received measurement data;        selecting at least one parameter set based on the rating;        computing the position of the end of the traffic jam on the basis of the at least one selected parameter set;        sending the position of the end of the traffic jam to a/the vehicle.        
Similar or identical advantages are obtained to those already described in conjunction with the server and the system.
A further preferred method comprises the steps of:                generating, preferably randomly generating, further parameter sets on the basis of the at least one selected parameter set, particularly within prescribed ranges of variation;        receiving further measurement data for at least the vehicle or for a further vehicle;        rating the quality of at least some of the sigmoid functions defined by the further parameter sets based on the received second measurement data;        selecting at least one further parameter set based on the rating;        computing the position of the end of the traffic jam on the basis of the at least further selected parameter set;        sending the position of the end of the traffic jam to a/the vehicle or a/the further vehicle.        
New parameter sets can be generated by virtue of the eight parameters per parameter set each being slightly altered at random with a certain level of noise. This measure allows a multiplicity of different parameter sets to be produced again. As a result of the previously selected parameter set, the new parameter sets represent the traffic state in an improved and adapted form in comparison with the first parameter sets. As a result of fresh rating and selection of the parameter sets, it is possible for the position of the end of the traffic jam that was computed in a first step to be determined in an even more concrete form and more exactly by this second step. The generation of new parameter sets, the collation and rating of these new parameter sets with always new measurement data can be repeated as often as desired. Therefore, not only is it possible for the position and also the characteristic of the end of the traffic jam to be determined ever more exactly, the current changing circumstances are at the same time also repeatedly adapted.
The object according to the invention is furthermore achieved by a computer-readable storage medium that has executable instructions that prompt a computer to implement the method already described when said instructions are executed. Similar or identical advantages to those already described in conjunction with the server, the system and the method are obtained.
Other objects, advantages and novel features of the present invention will become apparent from the following detailed description of one or more preferred embodiments when considered in conjunction with the accompanying drawings.